Optimization of Major Process Parameters for Surface Roughness of ASTM 25 Grey Cast Iron using Taguchi method

Abstract

In this paper, the effect of machining process parameters on surface roughness of ASTM 25 grade grey cast iron during turning operation was investigated. Taguchi design of experiments, analysis of variance and multiple regression models were used to support this. The turning experiment was conducted on the grey cast iron shaft using coated carbide insert as cutting tool in a bid to achieve a low surface roughness. Turned surfaces were generated by varying the cutting speed, feed rate and depth of cut using LI 6 orthogonal experimental matrix data. The average roughness of the machined surfaces was measured al three different locations using a model SRT-6200 surface profilometer with a 0.8 mm cul off length. The results showed that feed rate was the most dominant among factors affecting surface roughness followed by cutting speed while depth of cut has a negligible effect. Surface roughness decreases as the feed rate decreases with increasing cutting speed and the best surface roughness value of I. I 75µm was observed using 0.272 mm/rev feed rate, 150 mlm in cutting speed and 0.6 mm depth of cut. A third-order multiple regression model was generated which closely predict the roughness values with a coefficient of determinant, R2 value of 0.96.